Job Details

Job Description:

Pay Range: $48hr - $52hr

Responsibilities:

• Design, develop, and maintain logical and physical data models to support enterprise applications.
• Collaborate with business analysts, architects, and developers to translate business requirements into robust, scalable data structures.
• Ensure data integrity, normalization, and optimization for performance, reliability, and scalability.
• Work closely with ETL developers and data engineers to implement data models within enterprise data warehouses, data lakes, and operational systems.
• Document data models, relationships, business rules, and metadata in alignment with enterprise architecture and compliance standards.
• Participate in data governance initiatives, ensuring adherence to security, privacy, and compliance requirements, especially for PHI/PII in a healthcare environment.
• Conduct data profiling, assess source system quality, identify data issues, and define data quality (DQ) rules and transformation logic.

• 5+ years of experience in data modeling, data architecture, or database design roles.
• Strong expertise in data modeling tools such as ERwin, PowerDesigner, or equivalent.
• Proficiency with SQL-based databases (e.g., Oracle, SQL Server, PostgreSQL).
• Solid understanding of data warehousing concepts, dimensional modeling, normalization techniques, and relational data structures.
• Familiarity with the Azure Cloud platform and modern data architectures including Data Lakes and Enterprise Data Hubs (EDH).
• bility to interpret business requirements and convert them into technical specifications and actionable data model designs.
• Understanding of API integration and common data exchange formats such as JSON and XML.
• Excellent communication and collaboration skills for working with cross-functional business and technical teams.

• Experience with healthcare payer data domains such as claims, provider, and member data.
• Exposure to data governance frameworks and Master Data Management (MDM) solutions.
• Proficiency in performance tuning, query optimization, and designing high-performance data structures.